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Updated: Mar 20, 2026

Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts
Published on: July 25, 2020
Development and clinical application of an integrative genomic approach to personalized cancer therapy
Andrew V Uzilov1, Wei Ding1, Marc Y Fink1,2
1Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
Background:
Personalized therapy provides the best outcome of cancer care and its implementation in the clinic has been greatly facilitated by recent convergence of enormous progress in basic cancer research, rapid advancement of new tumor profiling technologies, and an expanding compendium of targeted cancer therapeutics.
Methods:
We developed a personalized cancer therapy (PCT) program in a clinical setting, using an integrative genomics approach to fully characterize the complexity of each tumor. We carried out whole exome sequencing (WES) and single-nucleotide polymorphism (SNP) microarray genotyping on DNA from tumor and patient-matched normal specimens, as well as RNA sequencing (RNA-Seq) on available frozen specimens, to identify somatic (tumor-specific) mutations, copy number alterations (CNAs), gene expression changes, gene fusions, and also germline variants. To provide high sensitivity in known cancer mutation hotspots, Ion AmpliSeq Cancer Hotspot Panel v2 (CHPv2) was also employed. We integrated the resulting data with cancer knowledge bases and developed a specific workflow for each cancer type to improve interpretation of genomic data.
Results:
We returned genomics findings to 46 patients and their physicians describing somatic alterations and predicting drug response, toxicity, and prognosis. Mean 17.3 cancer-relevant somatic mutations per patient were identified, 13.3-fold, 6.9-fold, and 4.7-fold more than could have been detected using CHPv2, Oncomine Cancer Panel (OCP), and FoundationOne, respectively. Our approach delineated the underlying genetic drivers at the pathway level and provided meaningful predictions of therapeutic efficacy and toxicity. Actionable alterations were found in 91 % of patients (mean 4.9 per patient, including somatic mutations, copy number alterations, gene expression alterations, and germline variants), a 7.5-fold, 2.0-fold, and 1.9-fold increase over what could have been uncovered by CHPv2, OCP, and FoundationOne, respectively. The findings altered the course of treatment in four cases.
Conclusions:
These results show that a comprehensive, integrative genomic approach as outlined above significantly enhanced genomics-based PCT strategies.
Insights
A comprehensive genomic approach significantly improves personalized cancer therapy (PCT) by identifying more actionable alterations than standard methods. This integrative strategy enhances treatment predictions and outcomes for cancer patients.
Area of Science:
- Oncology
- Genomics
- Precision Medicine
Background:
- Personalized therapy offers optimal cancer care outcomes.
- Advancements in cancer research, tumor profiling, and targeted therapeutics facilitate clinical implementation.
- Integrative genomics is key to understanding tumor complexity.
Purpose of the Study:
- To develop and evaluate a personalized cancer therapy (PCT) program using an integrative genomics approach.
- To characterize tumor complexity through comprehensive genomic profiling.
- To identify somatic mutations, copy number alterations, gene expression changes, gene fusions, and germline variants.
Main Methods:
- Whole exome sequencing (WES) and SNP microarray genotyping of tumor and normal specimens.
- RNA sequencing (RNA-Seq) for gene expression and fusion analysis.
- Ion AmpliSeq Cancer Hotspot Panel v2 (CHPv2) for mutation hotspots, integrated with knowledge bases and cancer-type specific workflows.
Main Results:
- Identified a mean of 17.3 cancer-relevant somatic mutations per patient, significantly more than targeted panels.
- Found actionable alterations in 91% of patients (mean 4.9 per patient), including mutations, CNAs, gene expression changes, and germline variants.
- Genomic findings altered treatment course in four cases, demonstrating clinical utility.
Conclusions:
- Comprehensive, integrative genomic profiling significantly enhances genomics-based PCT strategies.
- This approach provides a deeper understanding of tumor drivers and improves therapeutic predictions.
- The study highlights the value of multi-omic data integration for personalized cancer treatment.
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